7 citations · 10 across the 6 of their papers we have counts for
4 papers · 1 filter
Latent Traits and Cross-Task Transfer: Deconstructing Dataset Interactions in LLM Fine-tuning
Shambhavi Krishna, Atharva Naik, Chaitali Agarwal +3
Large language models are increasingly deployed across diverse applications. This often includes tasks LLMs have not encountered during training. This implies that enumerating and…
Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming
Mrinank Sharma, Meg Tong, Jesse Mu +40
Large language models (LLMs) are vulnerable to universal jailbreaks-prompting strategies that systematically bypass model safeguards and enable users to carry out harmful processes…
Towards Generating Informative Textual Description for Neurons in Language Models
Shrayani Mondal, Rishabh Garodia, Arbaaz Qureshi +2
Recent developments in transformer-based language models have allowed them to capture a wide variety of world knowledge that can be adapted to downstream tasks with limited resourc…
Matching Pairs: Attributing Fine-Tuned Models to their Pre-Trained Large Language Models
Myles Foley, Ambrish Rawat, Taesung Lee +3
The wide applicability and adaptability of generative large language models (LLMs) has enabled their rapid adoption. While the pre-trained models can perform many tasks, such model…